Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_statfun_actvsblT”.

  FT_STATFUN_ACTVSBLT calculates the activation-versus-baseline T-statistic on the
  biological data (the dependent variable), using the information on the independent
  variable (ivar) in design.
  Note that it does not make sense to use this test statistic when baseline
  correction was performed by subtracting the mean of the baseline period from the
  whole data (for ERP data) or by dividing by the mean (for TFR data). If baseline
  correction is desired, you should subtract the full baseline and activation period.
  Use this function by calling one of the high-level statistics functions as
    [stat] = ft_timelockstatistics(cfg, timelock1, timelock2, ...)
    [stat] = ft_freqstatistics(cfg, freq1, freq2, ...)
    [stat] = ft_sourcestatistics(cfg, source1, source2, ...)
  with the following configuration option
    cfg.statistic = 'ft_statfun_actvsblT'
  Configuration options
    cfg.computestat    = 'yes' or 'no', calculate the statistic (default='yes')
    cfg.computecritval = 'yes' or 'no', calculate the critical values of the test statistics (default='no')
    cfg.computeprob    = 'yes' or 'no', calculate the p-values (default='no')
  The following options are relevant if cfg.computecritval='yes' and/or
    cfg.alpha = critical alpha-level of the statistical test (default=0.05)
    cfg.tail  = -1, 0, or 1, left, two-sided, or right (default=1)
                cfg.tail in combination with cfg.computecritval='yes'
                determines whether the critical value is computed at
                quantile cfg.alpha (with cfg.tail=-1), at quantiles
                cfg.alpha/2 and (1-cfg.alpha/2) (with cfg.tail=0), or at
                quantile (1-cfg.alpha) (with cfg.tail=1).
  Design specification
    cfg.ivar  = row number of the design that contains the labels of the conditions that must be
                compared (default=1). The first condition, indicated by 1, corresponds to the
                activation period and the second, indicated by 2, corresponds to the baseline period.
    cfg.uvar  = row number of design that contains the labels of the units-of-observation (subjects or trials)
                (default=2). The labels are assumed to be integers ranging from 1 to
                the number of units-of-observation.